In order to assess the quality of our predicted covariances on trajectories we take a multi-step approach.
First, we compose ICP estimates to generate the final pose as \(^0\hat{{\mathbf {T}}}_f\ =\ ^0\hat{{\mathbf {T}}}_1\ ^1\hat{{\mathbf {T}}}_2 \cdots \ ^{f-1}\hat{{\mathbf {T}}}_f\)  for a sequence with \(f\)  poses.
The ground truth final pose \(^0{\mathbf {T}}_f\)  is computed similarly.
We propagate the covariance associated to each estimate using the 4th order approximation, as in [1]}, to obtain an uncertainty estimate for the final ICP pose.
This way, it is possible to evaluate the Mahalanobis distance (Eq. REF ) in a spatially consistent manner.
The results are shown in Table REF .
They are only slightly optimistic, which is a remarkable outcome given the length of KITTI trajectories (up to more than 2km).
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